5results about How to "Accurate score" patented technology

The invention discloses a commodity scoring method and device and a related product. The method comprises the steps of obtaining feedback data of an object on a target commodity and a plurality of target commodity orders associated with the feedback data; based on the feedback data and a plurality of target commodity orders associated with the feedback data, obtaining an experience type and an emotion type of each target commodity order; the experience type of each target commodity order is used for indicating the experience feedback of the object on the target commodity in the target dimension, and the emotion type of each target commodity order is used for indicating the satisfaction degree of the object on the target commodity; and generating a score of the target commodity based on the experience types corresponding to the plurality of target commodity orders and the emotion types corresponding to the plurality of target commodity orders. Therefore, based on the analysis of the feedback text, the score is generated by comprehensively considering the experience feedback of the user on the target commodity in different dimensions and the satisfaction degree of the user on the target commodity, the relevance between the score and the feedback text is enhanced, and the scoring accuracy can be improved.

This invention discloses a method, storage medium, and device for batch re-grading of test questions. By extracting and reusing the standard question stem from a single assignment, it avoids repeatedly identifying the question stem for each assignment, significantly improving processing efficiency. By cropping and stitching together the clean answer traces of all students to form an aggregated image, it achieves a highly efficient "one-time input, batch grading" mode. Combined with a multimodal grading model, it can simultaneously understand the question requirements and each student's handwritten answer, accurately score, and generate feedback. With the addition of a caching mechanism and dynamic batching strategy, it can also adapt to different scales of re-grading needs, saving computing resources. This invention can significantly reduce the burden on teachers overall, improve the consistency and intelligence of grading, and is particularly suitable for teaching scenarios such as exam review and unified grading.

The application provides a user security level determination method and device based on user service change, which comprises the following steps: inputting user feature data of candidate users in a candidate user group into a trained user screening model to obtain a first user score for representing change probability of specific business service of the user; determining a specific user in the candidate user group according to the first user score; determining a second user score according to the first user score and the user feature data of the specific user; and determining a security level of the specific user based on the first user score and the second user score. The application determines possible change conditions of services that the user can enjoy from the condition that the user enjoys changed services, effectively quantifies change condition information of the user's demand for internet services from the dimension of change condition information of the specific business service from nothing to something, and can accurately determine the security level of the specific user and change condition information thereof.

Embodiments of the present application provide a model training and content display method and device, equipment and medium, relating to the technical field of artificial intelligence. The method comprises: obtaining a training sample set, the training sample set comprising a plurality of original content samples carrying labels, the plurality of original content samples being generated from target data, the number of clicks of the target data being less than a preset threshold, and the label representing the click probability of the target data; adding perturbation information to the plurality of original content samples to obtain a plurality of adversarial content samples; inputting the plurality of original content samples and the plurality of adversarial content samples into a click rate estimation model respectively to obtain a plurality of first gradients corresponding to the plurality of original content samples and a plurality of second gradients corresponding to the plurality of adversarial content samples; and adjusting parameters of the click rate estimation model according to the plurality of first gradients and the plurality of second gradients. The technical solution provided by the embodiments of the present application can improve the content recommendation effect and improve the search efficiency of users.

The application belongs to the technical field of artificial intelligence, and discloses a team cooperation optimization method, device, equipment and storage medium, the team cooperation optimization method comprises the following steps: inputting human time sequence characteristics in team interaction video into a time sequence behavior analysis and evaluation model to output a score of a preset team cooperation index corresponding to the team interaction video; analyzing an emotional index of a target team for the team cooperation index according to key cooperation data related to the team cooperation index; adjusting the score of the team cooperation index according to the emotional index; and generating a cooperation optimization strategy for optimizing the score of the team cooperation index. The application can be applied to financial technology, medical health and other business management systems, solves the problems of human bias in the evaluation process and the inability to evaluate in real time in the prior art, and solves the technical problem that optimization of team cooperation based on evaluation results cannot truly achieve optimization.